Abstract Suicide is now the second leading cause of death in youth aged 10-24 years, accounting for more deaths in this age group than all those for ten other leading causes of death combined. The vision of the U.S. Surgeon General and the National Action Alliance for Suicide Prevention (Action Alliance) is ?a nation free from the tragic experience of suicide.? In pursuit of this vision, the Action Alliance's Research Prioritization Task Force (RPTF) released a research agenda aimed at reducing suicide deaths and suicide attempts 20 percent by 2025. To achieve this ambitious goal, the RPTF has recommended strategically targeting interventions at population subgroups at high risk for suicide in designated ?boundaried settings?. Youth in publicly funded systems of care (e.g., Medicaid, child welfare, juvenile justice, and behavioral health) represent an especially large and important ?boundaried population? at heightened risk of suicide and mental illness relative to youth in the general population. Unfortunately, despite the large numbers of vulnerable youth in publicly funded programs, little is known about the rates and predictors of suicide for this population. This research project proposes to create, for the first time, an integrated population-based database that links 9 years of data across multiple Ohio child-serving agencies. This is a unique suicide prevention resource currently unmatched by any federal data system. This research has the potential to provide in depth prospective information concerning interactions between dynamic individual and contextual factors that might be fruitfully applied to the development of targeted suicide prevention and intervention programs. Specific aims of this proposed research are three-fold: 1) to quantify the incidence of suicide across and within 4 public child-serving systems in Ohio; 2) to identify high risk periods for suicide among youth in publicly funded sectors; and 3) to develop and validate a risk prediction algorithm to estimate individual risk for suicide in this population. Our central hypothesis is that entry to and exits from child welfare and juvenile justice programs will be associated with increased risk for suicide as will major transitions across levels of mental health care (e.g., moving from inpatient to outpatient). This retrospective longitudinal cohort study will use data on 2.2 million youth in public child serving systems aged 10-24 years who will be followed from 2010 to 2018. We employ a novel multistate statistical modeling approach to test hypotheses about transitions of care (Aim 2) and time-dependent Cox regression to examine predictors of suicide for youth in public child serving systems (Aim 3). The results of this innovative study will identify high-risk transition periods and contribute to a better understanding of risk for suicide among youth in publicly funded systems. Feasibility is supported by an existing commitment from our state partners to provide the linked data necessary to accomplish our objectives.